Many industrial applications such as electronic assembly and semiconductor manufacturing process require automatic alignment of printed circuit board or semiconductor substrates such as wafers. The alignment can be performed using pre-defined fiducial marks. This requires the make and introduce of the marks into the objects. This process limits the flexibility of the alignment options and increases system complexity. It is desirable to use a portion of the design structures of the object as templates for alignment purpose without specific design of fiducial marks. This removes the extra steps required to produce and insert the special fiducial marks.
The images of design structures of an object such as circuit board or a region of a semiconductor substrate can be acquired for alignment processing. However, the acquired images often exhibit low contrast and may be blurry or noisy in practical applications due to process variations and non-uniform illumination and noisy imaging system due to cost constraint or practical limitations. In this case, both the template selection and the template searching processes could be challenging.
A good template should have unique structures to assure that it will not be confused with other structures. It also needs to have stable and easily detectable features to ease the template searching process. This demands an automatic method and process for the selection of template from the design structures of an object.
The automatic generated templates must be “stable” so that the search algorithm rarely misses the correct template location even if the contrast of the image varies. This is challenging since the images for template generation could include any customer designed patterns.
A prior art fast multi-resolution automatic template generation and search method is disclosed in Oh and Lee, “Automatic template generation and searching method”, U.S. Pat. No. 6,603,882, Aug. 5, 2003. It generates a multi-resolution image representation from the input image. Automatic multi-resolution template search using lower resolution results to guide higher resolution search.
However, in the application where the common area that can be always observed is small due to large positioning error, it becomes very difficult to find unambiguous pattern for Pattern Search Alignment (PSA). This is a major problem that could fundamentally hinder the practical use of the PSA.